This paper describes the results of the working group investigating the issues of empirical studies for evolving systems. The groups found that there were many issues that were central to successful evolution and this...
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This paper describes the results of the working group investigating the issues of empirical studies for evolving systems. The groups found that there were many issues that were central to successful evolution and this concluded that this is a very important area within software engineering. Finally nine main areas were selected for consideration. For each of these areas the central issues were identified as well as success factors. In some cases success stories were also described and the critical factors accounting for the success analyzed. In some cases it was later found that a number of areas were so tightly coupled that it was important to discuss them together.
Describes recurrent plausibility networks with internal recurrent hysteresis connections. These recurrent connections in multiple layers encode the sequential context of word sequences. We show how these networks can ...
Describes recurrent plausibility networks with internal recurrent hysteresis connections. These recurrent connections in multiple layers encode the sequential context of word sequences. We show how these networks can support text routing of noisy newswire titles according to different given categories. We demonstrate the potential of these networks using an 82 339 word corpus from the Reuters newswire, reaching recall and precision rates above 92%. In addition, we carefully analyze the internal representation using cluster analysis and output representations using a new surface error technique. In general, based on the current recall and precision performance, as well as the detailed analysis, we show that recurrent plausibility networks hold a lot of potential for developing learning and robust newswire agents for the internet.
HyValue is a hybrid electronic submission system which utilizes techniques from natural language processing, neural networks and rule based systems to accept, evaluate and mark work submitted by a student for reading ...
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HyValue is a hybrid electronic submission system which utilizes techniques from natural language processing, neural networks and rule based systems to accept, evaluate and mark work submitted by a student for reading or writing. This paper describes the theory behind the system design and the development of the individual components and their interaction. Issues addressed include the definition of sentence structure, fuzzy rule construction and integration with a knowledge base containing the marking rubrics for reading and writing. An evaluation of the system is provided and conclusions drawn.
The key to a successful proof often lies within the analysis of failed proof attempts. Motivated by this observation we have developed and evaluated an interface to an inductive theorem prover which supports a collabo...
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The key to a successful proof often lies within the analysis of failed proof attempts. Motivated by this observation we have developed and evaluated an interface to an inductive theorem prover which supports a collaborative style of failure analysis. Our work builds upon an automatic proof patching mechanism and extends the capabilities of an existing theorem proving interface. Our approach is multi-disciplinary, we draw upon work from both the automated theorem proving and human computer interaction communities.
The reengineering of legacy systems - by which we mean those that have value and yet `significantly resist modification and evolution to meet new and constantly changing business requirements' - is widely recogniz...
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The reengineering of legacy systems - by which we mean those that have value and yet `significantly resist modification and evolution to meet new and constantly changing business requirements' - is widely recognized as one of the most significant challenges facing software engineers. A complex mixture of business and technical factors must be taken into account to ensure success, and there is a wide range of different contexts each with its own problems. Moreover, the business needs do not stay constant while the technical factors are dealt with. In the paper it is argued that the main problem is not that the necessary expertise does not exist, but rather, that it is hard for software engineers to become expert in all of the necessary areas. It is proposed that systems reengineering patterns may help to codify and disseminate expertise, and that this approach has some advantages over conventional methodological approaches. This contention is supported by means of some candidate patterns drawn from the authors experience and supported by information from elsewhere.
The use of multivariate information visualization techniques is intrinsically difficult because the multidimensional nature of data cannot be effectively presented and understood on real-world displays, which have lim...
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This paper describes the design and implementation of a computer-assisted learning tool to support the learning environment provided for postgraduate students following courses in Information Technology. The tool is c...
This paper describes the design and implementation of a computer-assisted learning tool to support the learning environment provided for postgraduate students following courses in Information Technology. The tool is called 'ICITT' - an acronym for Interactive Computerized Information Technology Tutor. The paper presents the unique aspects of this tool and the overall educational benefits of the system are briefly discussed.
From the Publisher: This book presents a selection of recent progress, issues, and directions for the future of case-based reasoning. It includes chapters addressing fundamental issues and approaches in indexing and r...
ISBN:
(纸本)9780262621106
From the Publisher: This book presents a selection of recent progress, issues, and directions for the future of case-based reasoning. It includes chapters addressing fundamental issues and approaches in indexing and retrieval, situation assessment and similarity assessment, and in case adaptation. Those chapters provide a "case-based" view of key problems and solutions in context of the tasks for which they were developed. It also presents lessons learned about how to design CBR systems and how to apply them to real-world problems. The final chapters include a perspective on the state of the field and the most important directions for future impact. The case studies presented involve a broad sampling of tasks, such as design, education, legal reasoning, planning, decision support, problem-solving, and knowledge navigation. In addition, they experimentally examine one of the fundamental tenets of CBR, that reasoning from prior experiences improves performance. The chapters also address other issues that, while not restricted to CBR per se, have been vigorously attacked by the CBR community, including creative problem-solving, strategic memory search, and opportunistic retrieval. This volume provides a vision of the present, and a challenge for the future, of case-based reasoning research and applications.
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